Same code taking 15x longer to execute on a faster machine

2022 11 16
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更新时间：2022 11 17
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I recently upgraded to a faster computer (from a 16Gb i7 processor to a 32Gb RYZEN processor with a 16Gb NIVIDIA RTX GPU (CUDA compatible)).
I used to execute the following code in a matter of 5-10 seconds on my older machine (MATLAB 2021a). Now it is taking >2 minutes on a way faster machine (MATLAB 2022b).
I think it is related to a certain memory allocation setting in MATLAB which I might have applied on my previous machine, but I can't remember it anymore.
Is there someone who could help me in resolving this issue, please? For example, which setting I could modulate to execute this code faster?
Or is it is related to the MATLAB version?
dE00=zeros(6,7362497,"single"); %dE00 refers to a numerical value of color difference
% lab_NF contains six CIELAB color values (L*, a* and b*) while labDB is a
% database of 7362497 CIELAB color values.
for nClrs=1:7362497
dE00(1:6,nClrs)=deltaE2000(lab_NF(1:6,1:3),labDB(nClrs,1:3));
end
Thanks in advance!

17 个评论
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DGM
DGM 2022-11-16
编辑：DGM 2022-11-16
What function are you using? It's not either of these
https://github.com/debuglevel/MatLab-Image-Analyses/blob/master/deltaE2000.m
https://github.com/scienstanford/iqmetrics/blob/master/SCIELAB_FR/deltaE2000.m
because those doesn't support the way you're using it.
It's not this one
https://www.mathworks.com/matlabcentral/fileexchange/65536-camera-color-accuracy-analysis
because that doesn't either, and it doesn't return the same size output.
So what is it?
Aiman Raza
Aiman Raza 2022-11-17
Indeed, it is neither of the functions provided by you, I wrote my own DeltaE2000 code as per the original article
https://doi.org/10.1002/col.20070. I have attached the function though I am still wondering if it is the code that is poorly written, it should work even badly on a slow machine, not the opposite. My code works fine and it can take the inputs in a versatile manner. It is just very slow as compared to my old machine which is a big disadvantage for me, since I will be running this snippet multiple times.
Thanks !
Bruno Luong
Bruno Luong 2022-11-17
编辑：Bruno Luong 2022-11-17
What is the spec of the older computer? I guess it's intel base? Some people complain the slowness of AMD proessor possibly due to the library.
Have you run
bench
command?
I believe TMW claims many operations of small matrices is faster on R2022b (see the release note).
There is memory setting for java heap space, but I don't think it affects the computation speed.
Bruno Luong
Bruno Luong 2022-11-17
编辑：Bruno Luong 2022-11-17
BTW I run your code with random input
dE00=zeros(6,7362497,"single"); %dE00 refers to a numerical value of color difference
% lab_NF contains six CIELAB color values (L*, a* and b*) while labDB is a
% database of 7362497 CIELAB color values.
lab_NF = rand(6,3,'single');
labDB = rand(7362497,3,'single');
tic
for nClrs=1:7362497
dE00(1:6,nClrs)=deltaE2000(lab_NF(1:6,1:3),labDB(nClrs,1:3));
end
toc
It takes 90 seconds on my computer (Intel + Windows 11 + R2022b)
Aiman Raza
Aiman Raza 2022-11-17
Thanks for your comment. Now that you say that, I do think the AMD processor could be the issue. Earlier I had an intel xeon i7 processor with half the RAM and no GPU and the same command worked better.
I ran the bench command and it shows clear superiority for sparse/2D and 3D operations for a simimar intel i7 processor. Only if I knew this before buying this expensive computer.
JAVA heap space would also reduce available memory for storing arrays, so I am a bit not sure about it.
Any other workaround? Should I try updating to Win 11 or degrading to MATLAB 2021a?
Bruno Luong
Bruno Luong 2022-11-17
I don't believe the MATLAB version has anything to do with it. I see constant improvement of speed over time, but nothing that can explain x 15. Also your code does seem to use any gpu so Nvidia card is irrelevant.
Aiman Raza
Aiman Raza 2022-11-17
Exactly, the GPU isn't involved so I think it is clearly an issue with Intel vs AMD. Though 90s is an improvement over 2.5 minutes, but slower than 5s-10s.
Do you think I could write this snippet better? I mean just this loop to perform faster or without loop with vectorisation?
Bruno Luong
Bruno Luong 2022-11-17
I don't want to answer speeding up your code here. It's off topic.
Aiman Raza
Aiman Raza 2022-11-17
Thanks for your help though, it makes more sense to why my code suddenly runs slower. Have a great day!
Star Strider
Star Strider 2022-11-17
This has been a problem for a while.
See a relevant discussion here: How can I use the BLAS and LAPACK implementations included in AMD Optimizing CPU Libraries (AOCL) with MATLAB R2022a? - .
The last posted Comment (posted about a month ago) expresses my frustration on this.
All of my computers have AMD processors because I prefer them.
.
Bruno Luong
Bruno Luong 2022-11-17
编辑：Bruno Luong 2022-11-17
@Star Strider can you please run the code (the one I posted) and post the result?
Aiman Raza
Aiman Raza 2022-11-17
Thank you for your suggestion. However for me using the BLAS/LAPACK did not change the timing. Unfortunately it still takes the same amount of time. PS: I double checked to make sure that the AOC libraries were correctly installed.
Bruno Luong
Bruno Luong 2022-11-17
What you should double check is this:
"I used to execute the following code in a matter of 5-10 seconds on my older machine "
Aiman Raza
Aiman Raza 2022-11-17
I ran the code on both the machines before posting my question, and it still holds true. I think I just have a poor processor for MATLAB. In python my code goes way faster than before.
Bruno Luong
Bruno Luong 2022-11-17
My laptop intel is quite recent, and it is no where 15 s, as I mention 90 seconds.
To be sure I'll download R2021a and do the same tic/toc.
Bruno Luong
Bruno Luong 2022-11-17
编辑：Bruno Luong 2022-11-17
I run gain the code on my Intel laptop
R2021a: 85 seconds
R2022b: 87 seconds
Aiman Raza
Aiman Raza 2022-11-17
So it clearly is my machine which is just not great. I will try to rewrite the code more smartly to improve the processing duration. Thanks a lot.

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 采纳的回答

Jan
Jan 2022-11-17
Ran in:

1 个投票

Ran in:
n = 32000; % 7362497;
dE00 = zeros(6, n,"single");
lab_NF = rand(6, 3, 'single');
labDB = rand(n, 3, 'single');
tic
for nClrs = 1:n
dE00(1:6, nClrs) = deltaE2000(lab_NF(1:6, 1:3), labDB(nClrs, 1:3));
end
toc
Elapsed time is 1.013390 seconds.
% Faster without explicit indexing:
tic
for nClrs = 1:n
dE00(:, nClrs) = deltaE2000(lab_NF, labDB(nClrs, :));
end
toc
Elapsed time is 0.722065 seconds.

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Aiman Raza
Aiman Raza 2022-11-17
编辑：Aiman Raza 2022-11-17
Thanks a lot! Removing the indexing did reduce the time to 106s. It is still better than before. I will try to code without a loop. That might further improve the timing.

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